Support Activities-Data Sharing Support

Research Fields,
Communities

Databases＜ Integrated Use of Life Science Database ＞-TogoDX（Life Science Data Explorer）-TogoVar（Japanese Genetic Variation Database）-RDF Portal（Life Sciences RDF Data List）-A suite of tools to support RDF data retrieval andcreation supporting the above

Life Sciences＜ Data on social conditions（social sciences）＞-Survey on Japanese national character-International comparative study of awareness-（On-site analysis lab）

Social survey data,
Microdata from public
surveys, Social big data

Activities

Establish an environment for the
integrated use of databases, develop
essential technologies for databaseintegration, and maintain international
standards＜ Integrated Database for Polar Science ＞-Science Database-Arctic and Antarctic Data archive System（ADS）-Inter-university Upper atmosphere Global
Observation NETwork（IUGONET）

Polar and Global
Environment＜ Creation of humanities（digital humanities）
disciplines based on data science ＞-Dataset of Japanese pre-modern text
-Dataset of Kuzushiji in Japanese pre-modern text
-Dataset of Edo Cuisine Recipes-Collection of Facial Expressions-Edo big data
-Database for Sharing Information about Historical
Materials

Digital Humanities,
Machine learning,
Art history,
Palaeoclimatology,
Japanese cultural studies-Data Analysis Support

Contribute to global environmental
research by promoting data science andthe publication and sharing of various
scientific data obtained from the Arctic
and Antarctic Regions

Research Fields,
Communities

Analysis objects＜ Genomic data analysis of various species ＞-New Genome Determination-Genome Re-sequencing-Transcriptome Analysis-Metagenomic Analysis

Genome Biology
Genome Medicine
Genomic Drug Discovery＜Theoretical and applied research based on
numerical simulations ＞-Human Flow Simulation-Spacecraft Simulation-Coastal Ocean Model-Integrated Transport Simulation of Nuclear Fusion
Plasmas-Magnetosphere-Ionosphere Model

Traffic Engineering
Space Engineering
Geophysics
Nuclear Fusion Studies
All other fields that use
data-centered science
concepts and methods

Inter-University Research Institute Corporation
Research Organization of Information and Systems

Joint Support-Center
for Data Science Research（ROIS-DS）

Formation of an inter-university network
infrastructure for effectively using data onsocial conditions（social surveys, public
micro databases, social big data）andcontribution to local communities.
Develop novel humanities research in theera of open science, such as data-driven
humanities, which analyses humanities
materials（historical documents）using
cutting-edge technologies in informatics
and statistics, as well as humanities big
data, which allows cross-disciplinary useof datasets built on humanities researchoutcomes

Activities

Provide informatics-based analyticalsupport for diverse life science researchbased on large amounts of sequence datafrom next-generation DNA sequencers
Research consultation and support andjoint research utilizing methods such asdata assimilation and emulators
Organize hands-on workshops andexperiential learning activities related tothe above

Joint Support-Center for Data Science Research（ROIS-DS）
10-3 Midori-cho, Tachikawa-shi, Tokyo 190-0014
https://ds.rois.ac.jp/en/
Tachikawa Academic Plaza Bus Stop
Tokyo District Court
Tachikawa Branch
Saibanshomae

Tama
MonorailatsuLocal Autonomy
College

Midoricho Kita
Park

Tak
am

ROIS-DS

Sta.

National Institute forJapanese Languageand InstituteContact: Data Science Promotion Section Tel: +81-42-512-9254

12

email: ds_suishin@rois.ac.jp

brochure 202303

1

Joint Support-Center for Data Science Research（ROIS-DS）-Cooperation, Collaboration, and Development -Interdisciplinary Resource-Sharing andSupporting Researchers with Data-driven

Joint Research Center for
Research
Hiroyuki Araki,

Center of ROIS for Promoting Data Science

Outline:Research Organization of Information and Systems “Joint Support-Center for Data Science Research（ROISDS）” is a resource-sharing and joint research center within ROIS that promotes data science nationwide on an
integrated basis, to solve scientific and social challenges through the advanced analysis of large-scale data.
Established in the fiscal year 2016 by ROIS, ROIS-DS boosts cooperation and collaboration with universities
and other organizations with a focus on data science（data-driven research）. As of 2022, ROIS-DS consists of six
centers, namely Database Center for Life Science（DBCLS）, Polar Environment Data Science Center（PEDSC）,
Center for Social Data Structuring（CSDS）, Center for Open Data in the Humanities（CODH）, Center for Genome
Informatics（CGI）and Center for Data Assimilation Research and Applications（CARA）, and contributes toenhancing the research capabilities of universities and other institutions. ROIS-DS handles an extensive rangeof data, from a large amount of bioinformatics data on genomes and genes to observation data obtained byatmospheric radar and pre-modern Japanese text, social surveys, and public microdata. Therefore, we arecarrying out our activities in cooperation with four research institutions which are subsidiary organizations ofROIS, namely National Institute of Polar Research, National Institute of Informatics, The Institute of Statistical
Mathematics, and National Institute of Genetics, as well as the other research institutions of the Inter-University
Research Institute Corporation.

Joint Support-Center for Data Science Research（ROIS-DS）
Director
Steering Committee
DS Liaison Council
Data Science Promotion Section（responsible for the management of the project promotion）

Data Sharing Support Group
Database Center for Life Science
Polar Environment Data Science Center
Center for Social Data Structuring
Center for Open Data in the Humanities

Data Analysis Support Group
Center for Genome Informatics
Center for Data Assimilation Research and Applications

2◆ Database Center for Life Science（DBCLS）◆
Promoting open science in the life science field and R&D forlife science database integration◆ Polar Environment Data Science Center（PEDSC）◆
Promoting resource-sharing to provide valuable data andits analytical support for those data on changes in the polar
environment and Earth system over a long-time axis from thepast to the present◆ Center for Social Data Structuring（CSDS）◆
Maintaining databases on social survey data, public survey
microdata, and social big data for university researchers. Also
creating communities for data usage to promote empiricalresearch for solutions to various social challenges, including
environment, public security, and economy◆ Center for Open Data in the Humanities（CODH）◆
Creating a new academic field for humanities based ondata science (digital humanities), as well as forming andenhancing research hubs beyond organizational boundaries
by promoting data-centric openness.
◆ Center for Genome Informatics（CGI）◆
Supporting data analysis to obtain biologically significant
information from a large amount of genome andtranscriptome data making full use of cutting-edge
bioinformatics technology◆ Center for Data Assimilation Research and Applications（CARA）◆
Solving problems in various sciences and industries throughthe data assimilation technique

Director of ROIS-DS

Support Project（Data Sharing Support）

Life science data sharing support project
Polar environmental science data sharing support project
Human and social science data sharing support project
Humanities open data sharing support project

Details of
our support
projects is on
page 12.

Support Project（Data Analysis Support）

Genomic data analysis support project
Data fusion computing support project
Human Resource Development（Training of Data Scientists）

Data science expert development
through on-the-job training
Training of data science educators（DSinstructors）
The Collaboration Program（ROIS-DS-JOINT）

Joint research program
Joint research meetingSee
page 10for moredetails.

Hub Activities:

Data Scientists Education andTraining Hub

President of ROIS

ROIS-DS and other institutions work
together to train data science experts
at various levels and in various fields

National Instituteof Polar Research

Support for world-class researchefficiency through cooperation andintegration between the ROIS-DS andNational Institute of Genetics（NIG）
regarding the collection, organization,
standardization, etc. of data

[Discipline-based human resource development] Developing
talent for polar data science, informatics-related data science,
biodata science, etc.

Biodata Science Initiative（BSI）

Japanese Culture Big Data
Research Hub

ROIS-DS and National Institutes for
the Humanities cooperate to analyse
Japanese culture using data-driven
methodologies

National Instituteof Informatics

The Institute of
Statistical
Mathematics

National Instituteof Genetics

National Institutefor Humanities

ROIS
-DS

National InstituteofJapanese Literature

Synergistic effects beyond institutions associatedwith the development programs for data science talent

Data Science
Education andTraining Hub
Commandcenter of humanresource
developmentfor ROIS

BiodataScience
Initiative（BSI）

Japanese
CultureBig Data
Research Hub

Biodata Hubof Japan

Big Data
Research Hub
for Integrated Arts
and Science

Upgrading Support for DS Research and Forming Research Hubs
人間文化研究機構

Promotion of data science through cross-organizational reform of ROIS with ROIS-DS asa core（synergy effects through collaboration and integration）

3

Data Sharing Support
Database Center for Life Science（DBCLS）

Polar Environment Data Science Center（PEDSC）

Field through Database Integration

To contribute to global environmental research, we promote
data science and the publication and sharing of various scientific
data obtained from the Arctic and Antarctic Regions.

To promote open science in the life science field, DBCLS conducts research anddevelopment on “database integration” so that universities, research institutions,and other organizations throughout the country can utilize and apply, in a centralizedmanner, the diverse and rapidly growing number of databases they owned andgenerated. We focus on creating knowledge graphs that standardize the terms used todescribe data and their classification systems（ontologies）, developing technical toolsthat extract effectively necessary information from these created knowledge graphs,
using efficient literature information management, and so on. We also invite expertsof database development organizations from around the world to organize annual
developers’ conferences such as BioHackathon, leading the international technicaldevelopment and standardization for integration.

The purpose of the Polar Environment Data Science Center（PEDSC）is to promote theopening publication and sharing of various types of scientific data originally obtainedby scientific observations and research activities in the Antarctic and the Arctic regions
by the polar science research community in various fields led by National Instituteof Polar Research（NIPR）, to strengthen the collaborations between universities
and other external communities, and to support the creation of further scientificoutputs and further advancement of the importance of the polar science research.
Internationally, PEDSC is also expected to play the key role of a national data centerfor polar science in Japan. The goals of PEDSC are to play a central role in the data
activities in the polar science research in Japan, to create a new data-centric polar
science, and to contribute to the advances of global environmental studies.

Promoting Open Science in the Life Science

A group photo taken at the domestic BioHackathon held in September
2022. In Kochi, 79 participants worked on various development projects.

■T hrough ROIS-DS-JOINT, DBCLS supports members of any university, research institute, company, etc.
who are interested in developing and applying the following technologies and related methods:

Keywords: [Life science data integration] [Knowledge graphs] [Large-scale data analysis]

4

Satellite data

Arctic Studies

Antarctic
Studies
極域環境データサイエンスセンターの活動内容
Antarctic Arctic
Data Management
Archives
DB Creation
Joint Research
Data Sharing
Open Data
Data Disclosure
Data Publication
Data Science
Data Visualization
Data Analysis

Space and
Upper
Atmospheric
Sciences

Geoscience

Polar
Meteorology
andGlaciology

Bioscience

PEDSC handles data obtained from all fields through scientific observation
and research activities in both the Arctic and the Antarctic Regions.

Activities of PEDSC
NiPR

Polar Science
Community

3. Time Series
Database
Observation &Research Activities▲

Implementing the integrated use requires collaboration
with national and international DB professionals.
Therefore, we have organized various workshops,
such as the international BioHackathon in which joint
development works were intensively performed over the
past decade. Despite the difficulty in holding international
events where international participants have to be invited
amid the COVID-19 pandemic, we continue to organize
domestic BioHackathon（annually）and SPARQLthon/Togothon（monthly, two consecutive days）to promote DB
standardization.

▲

Data analysis platform powered by TogoDX, a framework for exploring the knowledge
graph which integrates various databases

O n t h e ot h e r h a n d , st u d i e s s u c h a s g l o ba lenvironmental change may produce entirely new
results by simultaneously combining a wide variety ofdata from many different fields.
In such cases, meta-information on the location andattribute of those various data（metadata）should betreated in a unified manner. Also, it could be possiblethat data from a research field is applied to unrelated
research fields, which leads to unpredictable new
findings and new values. To this end, openness andsimple accessibility of the data are important. We aim
to support such activities for processing, analyzing,archiving, sharing, and opening polar science data
（to promote further collaboration with external
communities）.

Akira Kadokura,
Director of PEDSC

Activities of PEDSC▲

Data handled by PEDSC are obtained throughscientific observations and research activities in the
Antarctic and Arctic regions. Various observations andresearch activities are carried out in both polar regions
mainly by National Institute of Polar Research（NIPR）
in various research fields, including upper atmosphericsciences, meteorology, marine science, glaciology,
geoscience, and bioscience, and a wide diversity ofdata are obtained in various forms, such as digital data
in various recording media, or samples data obtained
and stored in various containers.
The obtained data are processed and analyzed andfrom which, after being converted to physicallymeaningful data, scientific results are generated.
In order to generate reliable scientific results, thereliability of the data should be ensured. For that
purpose, the data should be securely stored without
being lost, degraded or falsified, and be usable foreveryone, the reproducibility of the same scientificresults should be maintained, and so on.

▲

In order to realize the environment
under which databases（DBs）scatteredon the web can be utilized in an integrated
manner, we, striving to build knowledge
graphs of life science data, continuously
support transporting various data in
Resource Description Frameworks（RDF）
a n d a cce pt R D F d ata f ro m d i f fe re n torganizations. In 2021, we developed
TogoDX, a frame work for integrated
exploration of information accumulated
in various DBs, and made public TogoDX/
H u m a n（ h t t p s : / / t o g o d x . d b c l s . j p /human/）, an application enabling onestop exploration of information on humans
from a knowledge graph integrating
national and international databases. The
tool helps narrow down research targets,interpret and discuss experimental results,
and apply the narrowed-down results tointegrated analysis. Future development
will include the enhancement of data on
humans and the application of TogoDX toother species.

Yuji Kohara,
Director of DBCLS

4. Sample
Database

ROIS/ROIS-DS

PEDCS

1. Integrated
Database

2. Open (General Purpose) -Science Database-ADS
Database Systems-IUGONET

External
Communities-Universities-ResearchInstitutions-Companies-Society-International
Organization

5. Data Publication: Polar Data Journal
6. Cooperation with national and international communities
7. Promotion of Data Science and Joint Research

PEDSC bridges the various data activities between polar scienceand external communities.
http://pedsc.rois.ac.jp/en/activity■ Through ROIS-DS-JOINT, PEDSC supports members of any university, research institute, company,
etc., who are interested in using the following data and database systems:

Keywords: [Polar Science Data] [Science Database] [IUGONET]5

Data Sharing Support
Center for Social Data Structuring（CSDS）

Center for Open Data in the Humanities（CODH）

To Contribute to Solving Social Issues
through Maintaining and Sharing various Data Obtained
from Society

Promoting Open Science and Digital Innovationin the Humanities: Development of Data-Driven
Humanities and Humanities Big Data

The activities of the Center for Social Data Structuring（CSDS）are to maintain andmake available a wide range of data obtained from the measurement of various
phenomena in society—such as data obtained through social surveys targeting
individuals or organizations, official microdata collected as a result of statisticalsurveys conducted by the public sectors such as government agencies, and social big
data collected from real-time monitoring of social activities using various devices—,to put such data to a wide range of practical use, to promote empirical scholarshipfor the solution of various social issues, and to develop research infrastructure forthe implementation of policy making based on empirical data. The Center’s activities
also include developing basic technologies that facilitate data maintenance andutilization.

Center for Open Data in the Humanities（CODH）is advancing its research mainly
on two themes, aiming for the promotion of open science and digital innovationin the field of humanities. The first is the study of “data-driven humanities” that
innovates research methods of the humanities by applying cutting-edge data-driven
technologies in informatics and statistics. We create new knowledge from humanities
data through new technologies such as research on AI kuzushiji recognition for premodern Japanese text and research on art history using the International Image
Interoperability Framework（IIIF）. The second is the study of “humanities big data”
in which big data generated in the humanities field is used for research in otherfields. We are engaged in research on historical climatology, which involves retrieving
weather data from diaries in the Edo period to reconstruct the climate in the past.

Tadahiko Maeda,
Director of CSDS▲

CSDS conducts the following projects and initiatives in three main groups according to the fields from which data are available.

Social Survey Related Project

The project implements data collection
by forming a nationwide joint researchn e t w o r k a n d m a i n ta i n i n g a n ddisseminating social survey data. It
promotes projects on the maintenanceand publication of large-scale academic
research data inherited from the Instituteof Statistical Mathematics, researchplanning and data sharing of joint
surveys conducted with researchersof other organizations, and researchand dissemination of the compliancerelated issues associated with theadministration of the social surveys.

Official Microdata Project

The project is responsible for the
maintenance of official microdata and thedevelopment of resource-sharing systems,
R&D for online data analysis systems,
operation of an on-site analysis facility,
etc. It promotes research projects, such as
microdata security related to the securepublication of microdata, the promotionof secondary use of official statistics, theproject for synthesis credit risk databasein the economic and financial sector, andevidence-based policy making (EBPM)
using government statistics. It alsofunctions as the secretariat of ResearchConsosium for Official Microdata of Japan.

Social Big Data Project

The project maintains methods for
managing shared data and platforms,
which are needed for research activities
that use social big data among
researchers from different organizations.
In addition, it conducts joint researchusing social big data. In projects aiming
to develop a data-sharing infrastructurein the real world, we work withmunicipalities and other organizations
to empirically develop a data-sharing
infrastructure system that can efficiently
collect, monitor, and analyze the everchanging real-world conditions in social
infrastructure such as roads and traffic.

Exploratory Data
Analysis

Researcher

RemoteAccessVisit

On-site Facility
Safe
Analysis Result

Official
Microdatamiwo:
App for AI Kuzushiji Recognition

An app that uses AI to convert images ofcharacters written in cursive into modern
Japanese characters in seconds. Available
free of charge for iOS and Android.

Edo Big Data

Historical big data on the city of“Edo,” including commerce, tourism,
and individuals, are linked withgeographical data and integrated fordata-driven analysis of the past world.

IIIF Curation Platform

Introducing to the world of the
IIIF a new concept of curation andrealizing a user-driven IIIF platform.

Bukan Complete Collection

Creating an information platform fordaimyo（feudal lord）families andshogunate officials based on thecomprehensive analysis of Bukan, abestseller series for 200 years during theEdo period.

Asanobu Kitamoto,Director of CODH

Collection of Facial Expressions（KaoKore）

Using the IIIF Curation Viewer, facesthat appear in artwork are cut out
and gathered for use in art history
research.

Rekiske

Sharing knowledge and experience
about historical materials to promotematerial-based research in various
fields.

Data
Concealing

Safety Review

Analysis Result
Central Server

Outlput Checker
Lifecycle of Data

On-site analysis process■ Through ROIS-DS-JOINT, CSDS supports members of any university, research institute, company, etc. who
are interested in maintenance and resource-sharing related to the following data, and in development
and research of basic technologies related to various processes which lead to resource-sharing.
Keywords: [Social Survey Data] [Official Microdata] [Social Big Data]

6■ Through ROIS-DS-JOINT, CODH supports members of any university, research institute, company, etc.
who are interested in developing and applying the following technologies and related methods:

Keywords: [Pre-modern Japanese Text, Kuzushiji] [IIIF] [Humanities Big Data]

7

Data Analysis Support
Center for Genome Informatics（CGI）

CGI supports informatics analysis to extract
biologically meaningful information fromlarge amounts of genome and transcriptome data

Problem-solving through the integration of simulation andobservational data: Want to keep trying a simulation that doesn’t
work? How can observational data be used for prediction?

With the advancement of next-generation sequencing（NGS）technology, analyses using
NGS, such as novel genome sequencing, resequencing, and transcriptome analysis, havebeen widely conducted in various life science research fields. However, NGS data are only
fragmental data of base sequences, and the volume of such data is enormous. Therefore, inorder to efficiently analyze them and obtain results that meet the purposes, it is essential tohave knowledge and skills in bioinformatics in addition to knowledge of biology.
The Center for Genome Informatics（CGI）conducts research and development of
information science technology for the rapid and highly accurate analysis of large amountsof genome data and supports real data analysis using cutting-edge methods and trains
personnel for this purpose.

Data assimilation is a method of integrating observational data with numericalsimulations. It allows the development of a data assimilation system, simulations
that enable highly accurate predictions, and emulators, simulations that significantly
reduce processing time. The center offers a consultation service for data assimilation
research, providing in-person advice and technical guidance and support for problemsolving. Consultation and joint research are available for the data assimilation
method based on statistical science and for the application of data assimilation. We
are looking forward to your contact on how to deploy data assimilation or what to donext following data assimilation calculations.

（Japanese website）▲

CGI provides support to researchers ofuniversities, research institutions, etc, forvarious kinds of genomic data analyses（Fig. 1）.
During the six years from 2016 to 2021,
we provided analysis support for total of
51 tasks at the request of 32 universities
and research institutions（affiliatedinstitutions of the representative）.

▲

The genomic data handled are mainly
NGS sequence data, but the research
objectives and experimental conditions
vary widely depending on the study.
The target organism species also varyfrom mammals and other vertebrates to
insects, plants, fungi, and prokaryotes.
Therefore, appropriate analysis methods
must be selected according to genome
size, structure, and evolutionar ybackground. Taking advantage of ourrich analytical experiences, CGI provides
flexible and highly accurate analyticalsupport according to research objectives.

▲

In addition, we are committed
to securing an environment to
p r o v i d e c u tt i n g - e d ge a n a l y t i c a lmethods by developing, for smooth
implementation of analysis support,
various analysis pipelines, such as the
genome annotation pipeline（Fig. 2）
and the genome resequencing pipeline
as well as novel analytical methods,
including gene prediction methods,
RNA-seq assemblers, meta-genome
species classification, etc.

What We Analyze

Hideki Noguchi,
Director of CGI・Transcriptome analysis

・De novo genome sequencing
De novo genome assembly

Gene structure/expression analysis

Construct, by use of NGS data, genomes ofnovel organism species without reference
sequence

Conduct gene structure identification andgene expression quantitative analysis
through De Novo assemble mapping ofRNA-seq

Genome annotation

Identify and annotate gene location
on genomic sequence and exon-intron
structures

・Genome resequencing

Whole genome resequencing

non-coding RNA analysis

RNA secondary structure prediction,
targeted retrieval of miRNA, etc.

・Metagenomic analysis

Compare sequence reads of wholegenome to reference genome and detect
SNV and Structural Variation（SV）

Targeted genome sequencing/epigenetics analysis

Exom, RAD-seq, ChIP-seq, HiC-seq etc.

Metagenomic assembly

De novo assemble metagenomic sequencereads
Species classification, gene prediction

Metagenomic sequence clustering,
gene prediction, pathway analysis etc.

Genome data analysis performed at our center

Genomeassembly

PGAP

Protein database- UniRef��- Protein sequences of closely
related species- Longest-orf

�.P�A：Making alignments.

�.A�R：Making RGN-data.

�.R�G：Making gene models（“SPALN”-based custom
program）.

De novo transcriptome
assembly（trinity）
GenomeRNA-seq
assembly

Get longest-orf（TransDecoder）

Trinitiy.fasta

Ab-inito gene prediction

Protein sequences （ using Funannotate pipeline;v�.�.� ）by“A�R”selection
PGAP.gﬀ

PGAP_prot.gﬀ,PGAP_rnaseq.gﬀ,
PASA.gﬀ,Ab-initio.gﬀ

Integration of gene models：gMerge（In-house program）→DS-gap.gﬀ

Augustus training→PASA.gﬀ,Augustus parameter
Gene prediction step→Ab-initio.gﬀ

Integration of gene models：
EvidenceModeler→Fun_evm.gﬀ【On-the-spot relay of consultation】
Thank you for visiting us in Tachikawa.
Please give us about two hours.

I understand that you intend to deploy
data assimilation. It still needs to be
implemented in your field. Where did you
hear the term “data assimilation?” So,
you listened to my seminar. That’s nice tohear. So, you have a simulation model andobservational data.
All right, then please explain. Thank you. I
see, thank you very much.
Now, let me explain the concept of data
assimilation. I want to express all variables
in your material as x and all equations as f.
Is that OK? I’ll write it on the whiteboard.
Yes, x is a huge vector. I group variables
with different time steps separately. In thesame way, the data shall be taken together
as y.
Now, let us get to the main issue of data
assimilation. The problem is that x and y
do not match, so data assimilation uses y
to correct x. The difficulty with correctionis that a simple replacement of value x
with value y does not work. A number ofparameters are needed for the correction
to be carried out successfully. A simple
exercise will help you understand.
Do you want a sample program? For the
future, it is better to write a programfrom scratch. Please refer to the book
I mentioned. If your simulation is in
FORTRAN, it is also good to start data
assimilation in FORTRAN. Good luck!

Keywords: [Bioinformatics] [Next-generation Sequencing（NGS）] [Genomic DNA/RNA Data Analysis]

Genta Ueno,
Director of CARA

Inquiry(e.g. via website)

Consultation in Person

Issues, e.g.:- Improvement of simulation
performance using the data
- Gaining new insights fromdata and simulation- Efficient production throughthe integration ofexperimentation andsimulation

Implementation asa Joint Research Project

Provision of Expertise, etc.
If
Not Solved
SolvedPlease read the website and contact us by email for a research consultation.

Genome annotation pipelines■ Through ROIS-DS-JOINT, CGI supports members of any university, research institute, company, etc.
who are interested in developing and applying the following technologies and related methods:

8

Center for Data Assimilation Research and Applications（CARA）

Photo of the case settled■ Through ROIS-DS-JOINT, CARA supports members of any university, research institute, company, etc. who
are interested in developing and applying the following technologies and related methods:

Keywords: [Data Assimilation] [Simulation] [Emulator]

9

The Collaboration Program

The Collaboration Program “ROIS-DS-JOINT”

ROIS-DS invites applications every year for “ROIS-DS-JOINT” , an open joint research program on data science, to offer
researchers throughout the country opportunities for research sharing and joint research. There are two types of programs
offered: Joint Research to be conducted with researchers and resources from each center affiliated with ROIS-DS, and Joint
Research Meetings held mainly at each center, including research exchanges, workshops, etc.

The Joint Research Program-The principal investigator must be a researcher（including librarians, curators, and researchers at a museum or other⚫ ROIS-DS Workshop

The event is held to disseminate the outcomes of open joint research
projects. The second workshop was held online on January 2022（videoof the lecture is available on the DS facility website）. Following theinvited lectures in the first part and reports on the activities of eachcenter in the second part, the third part provided an opportunity for aposter session using the video chat tool, which led to active discussions
on the joint research outcomes.

institutions）at an educational or research institution other than ROIS

necessary to conduct the project such as consumables and cost of labors used at the host centers, for example.

The research coordinators of ROIS-DS play a central role in engaging in public
relations activities at conferences, response to inquiries, support for start-up of joint
research. They support the promotion of data science in a wide range of research
fields, including biology, medicine, pharmacy, engineering, agriculture, environmental
studies, earth and planetary sciences, statistics, and financial engineering.

Salary and the purchase of general equipment and consumables are not allowed.

The Joint Research Meeting Program-The principal investigator must be a member of an educational or research institution other than ROIS

The Molecular Biology Society of Japan, The Japanese Society of Human Genetics, The Japan
Society for Bioscience, Biotechnology, and Agrochemistry, Society of Evolutionary Studies, Japan,
The Pharmaceutical Society of Japan, The Ecological Society of Japan, Japanese Cancer Association,
The Society for Biotechnology, Japan, Japan Geoscience Union, Institute of Actuaries of Japan, The
Japanese Association of Risk, Insurance and Pensions, etc.

（the applicant could be someone whose primary responsibility is not research and development or surveying）⇒ e.g. Applicant can be a private sector researcher or local government officer

General remarks-Each proposal has to be discussed and agreed upon with the host scientist（s）prior to the submission.
-At least one of the ROIS-DS members has to be included in your proposal as the host scientist（s）.

Further information on the application and other instructions are provided on the ROIS-DS website（https://ds.rois.ac.jp/en_koubo/）.

The research funds
are managed by
DS centers, notallocated directly
to principal
investigators.

Information Dissemination⚫ Hands-on（Experimental Workshops）

We organize various hands-on workshops regularly
nationwide and internationally, including hands-on
training workshop for integrated database : AJACS（organized by JST NBDC and co-organized by DBCLS）,
RDF Workshop（organized by DBCLS）, CODH Tutorial（organized by CODH）and Data Assimilation hands-on（CARA, see photo）.

⚫ On-site Facility

Participating Universities coverage rate（by type of affiliated universities in the Joint Research Program. Cumulative numbers as of the end of March 2022）
National Universities: 34/86 universities（39.5％）
Public Universities: 10/97 universities（10.3％）

Private Universities: 31/627 universities（4.9％）
Note: university types are based on the list of institution numbers（https://www-kaken.jsps.go.jp/kaken1/kikanList.do）.

10

Made by Spatial Chat Ltd⚫ Coordination of research support-ROIS-DS will provide up to 1,000,000 JPY to each approved project as research expense, which is limited to the direct cost

-ROIS-DS will provide up to 500,000 JPY in total to each approved plan as expenses for travel and rental room fees, for example.

DS Promotion⚫ Publications

We published a booklet, ‘ROIS-DS: Steps towards Data
Science,’ featuring the history of ROIS-DS.
■ PR brochures（in Japanese）-ROIS-DS: Steps toward data science-ROIS-DS brochure-ROIS-DS Lecture Series'The Future of Data Science’Use of Facility

Joint Support-Center for Data Science Research（ROIS-DS）
offers, with the Center for Social Data Structuring（CSDS）,
an on-site research facility, equipped with an advanced
security environment such as access control systems andsurveillance cameras to ensure the safe use of survey
questionnaire information and confidential data.
＜Opening hours＞ Weekdays 10 am – 5 pm
Excluding Saturdays, Sundays, national holidays, 29 December
to 3 January, and holidays for which a booking calendar hasannounced a holiday notice.
*Open by agreement on holidays and after hours

11